Project on Type 2 diabetic and Hyperglycemic Pancreatic Islets

Introduction

Type 2 Diabetes (T2D) is a serious health concern. Identifying and understanding gene expression patterns associated with the disease can help uncover underlying biological mechanisms and could potentially support earlier detection.

Our analysis is focused on:

  • Identifying gene expression markers

  • Identifying key over- and under-expressed genes

  • Looking into co-expression of key genes

Data source:

“A Systems Genetics Approach Identifies Genes and Pathways for Type 2 Diabetes in Human Islets” (PMID: 22768844) (GEO ID: GDS4337)

Materials - Data Set Description

Data set overview:

  • 14481 different genes

  • 63 pancreatic islets samples

    • 9 with T2D

    • 54 controls

Descriptive statistics:

  • Similar mean gene expression across groups

  • Overall low mean expression levels

  • Slightly right-skewed distribution

  • => Testing for significant differential expression between the two groups

Materials - Wrangling

Frederik

Methods - Median Expression Differences

  • Goal: Identify genes with largest expression differences between T2D and control
  • Approach:
    • Compute median expression per gene for T2D and control samples
    • Calculate absolute differences between groups per gene
  • Visualization:
    • Plot 30 genes with the most different expressions
    • Bar plot and boxplots

Methods - p.values

Bolette

Results - Median

Lena

Results - p.value

  • Final p-value selection was p < 0.01

  • 635 genes labelled significant

  • Top 30 most significant (lowest p-vals) chosen for visualisation

Results - combined / correlation matrix

vælger 10 gener, correlation matrix

Bolette

Discussion / Conclusion

1) Difference in two methods

2) Sum up which genes are found by the analysis

3) does they support the litterature? uniprot…